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RSS FeedsEnergies, Vol. 12, Pages 1069: Generalised Regression Hypothesis Induction for Energy Consumption Forecasting (Energies)

 
 

20 march 2019 08:00:25

 
Energies, Vol. 12, Pages 1069: Generalised Regression Hypothesis Induction for Energy Consumption Forecasting (Energies)
 


This work addresses the problem of energy consumption time series forecasting. In our approach, a set of time series containing energy consumption data is used to train a single, parameterised prediction model that can be used to predict future values for all the input time series. As a result, the proposed method is able to learn the common behaviour of all time series in the set (i.e., a fingerprint) and use this knowledge to perform the prediction task, and to explain this common behaviour as an algebraic formula. To that end, we use symbolic regression methods trained with both single- and multi-objective algorithms. Experimental results validate this approach to learn and model shared properties of different time series, which can then be used to obtain a generalised regression model encapsulating the global behaviour of different energy consumption time series.


 
68 viewsCategory: Biophysics, Biotechnology, Physics
 
Energies, Vol. 12, Pages 1065: Analysis of the EU Residential Energy Consumption: Trends and Determinants (Energies)
Energies, Vol. 12, Pages 1068: Development of Nanofluids for Perdurability in Viscosity Reduction of Extra-Heavy Oils (Energies)
 
 
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